Mining social media data for opinion polarities about electronic cigarettes
Mining social media data for opinion polarities about electronic cigarettes
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DOI：
10.1136/tobaccocontrol-2015-052818
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发表时间：
2017-03-01
期刊：
影响因子：
5.2
通讯作者：
Hao, Jianqiang
中科院分区：
文献类型：
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作者：
Dai, Hongying;Hao, Jianqiang
背景电子烟的危害和好处一直在争论，近年来电子烟的使用迅速增加。通过将非商业性(有机)推文与商业性推文分开，我们试图评估公众对电子烟的态度。方法我们收集了2015年7月23日至10月14日期间(n=757)的推文，这些推文中包含“电子烟”、“电子烟”、“电子液体”、“电子烟”、“电子烟”、“蒸气”和“蒸发器”等词语。构建了一个多标签朴素贝叶斯模型，将推文分为5种极性(反对、支持、中立、商业、无关)。我们进一步分析了电子烟推文的普及率、推文的地域差异以及社会经济因素对公众对电子烟态度的影响。结果有机推文对电子烟的看法褒贬不一(反对17.7%，支持10.8%，中立19.4%)。这些反对有机吸烟的推文传递了关于使用电子烟风险的强烈教育信息，并呼吁普通公众，特别是年轻人，停止使用电子烟。然而，反对有机的推文数量超过商业推文和支持有机的推文的数量，比例超过1：3。有机推文的较高流行率与教育程度较高的州相关(r=0.60，p
Background There is an ongoing debate about harm and benefit of e-cigarettes, usage of which has rapidly increased in recent years. By separating non-commercial (organic) tweets from commercial tweets, we seek to evaluate the general public's attitudes towards e-cigarettes.Methods We collected tweets containing the words 'e-cig', 'e-cigarette', 'e-liquid', 'vape', 'vaping', 'vapor' and 'vaporizer' from 23 July to 14 October 2015 (n=757 167). A multilabel Naive Bayes model was constructed to classify tweets into 5 polarities (against, support, neutral, commercial, irrelevant). We further analysed the prevalence of e-cigarette tweets, geographic variations in these tweets and the impact of socioeconomic factors on the public attitudes towards e-cigarettes.Results Opinions from organic tweets about e-cigarettes were mixed (against 17.7%, support 10.8% and neutral 19.4%). The organic-against tweets delivered strong educational information about the risks of e-cigarette use and advocated for the general public, especially youth, to stop vaping. However, the organic-against tweets were outnumbered by commercial tweets and organic-support tweets by a ratio of over 1 to 3. Higher prevalence of organic tweets was associated with states with higher education rates (r=0.60, p